• Title/Summary/Keyword: Heuristic Value

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A Heuristic Algorithm for Flow Shop Layout Design (Flow Shop 배치설계를 위한 휴리스틱 알고리즘)

  • Nam, Kee-Ho;Ok, Chang-Hun;Seo, Yoon-Ho
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.34 no.4
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    • pp.129-137
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    • 2011
  • To date, facility layout problems has been solved and applied for job shop situations. Since flow shop has more restrictions, the solution space is much smaller than job shop. An efficient heuristic algorithm for facility layout problems for flow shop layouts is needed to be developed. In this thesis, a heuristic algorithm for rectangular bay layouts in a flow shop situation is presented. The proposed algorithm is developed by using slicing tree representation and applied to various flow shop layout problems. The effectiveness of the proposed algorithm in terms of exploration rate and objective function value are shown by comparing our results to simulated annealing.

A Study on the Perceived Value of Video Conferencing Platform: Focused on Heuristic-Systematic Model and Value-based Adoption Model (화상회의 플랫폼의 지각가치에 관한 연구: 휴리스틱-체계적 모델과 가치기반수용모델을 중심으로)

  • Tran, To-Diem-Hang;Kim, Min-Sook
    • Asia-Pacific Journal of Business
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    • v.12 no.2
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    • pp.205-222
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    • 2021
  • Purpose - Due to the Covic-19 pandemic, the perceived value of video conferencing platforms has been increased drastically. However, there is little guidance on how service providers can improve video conferencing platforms. The purpose of this study is to investigate the factors that influence the users' perceived value of video conferencing services based on the heuristic-systematic model and the value-based adoption model. Design/Methodology/Approach - In this paper, we theoretically explore the relationship of the antecedents of perceived value(credibility, expertise, attractiveness, economic feasibility, security, and interactivity) and its outcomes (perceived usefulness, perceived risk and perceived value). The outcomes of this research is a conceptualization of antecedents of perceived value supported by research hypothesis based on the existing literature. A total of 100 valid questionnaires were collected to empirically test the research model. Findings - The analysis results showed that credibility, economic feasibility, and interactivity positively influenced perceived usefulness. On the other hand, credibility, professionalism and interactivity negatively influenced perceived risk. Perceived usefulness positively affects perceived value and perceived risk has a negative effect on perceived value. The brand image as a moderating variable was found to decrease the effect of perceived risk on perceived value. Research Implications - The contribution of this study is significant for video conferencing providers as follows. First, a service provider can actively utilize influencers or referees with high credibility and expertise to maximize the perceived usefulness of users. Second, economic feasibility should be ensured in respect of users through various alliance discount strategies. Third, a video conferencing service company needs to build a positive brand image in order to increase users' perceived value.

The Problem of the Quality of the Predecessor Activity on the Time and Cost of the Successor Activity in the Project Schedule - Project Schedule with Resource Constraints - (프로젝트 일정에서 선행활동 품질이 후행활동의 시간과 비용에 미치는 문제 - 자원제약이 존재하는 프로젝트 일정문제 -)

  • Kim, Gab Sik;Bae, Byeong Man;Ahn, Tae Ho
    • Journal of Korean Society for Quality Management
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    • v.50 no.2
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    • pp.265-286
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    • 2022
  • Purpose: The time and cost of a project activity exists in a selected mode and there is a quality level for the selected mode, and the time and cost of the current activity is determined by the quality level of the preceding activity. When an activity is a predecessor activity of an activity, it is characterized as a trade-off problem in which the time and cost of the activity are determined according to the quality level of the activity. Methods: A neighbor search heuristic algorithm obtains a solution by (1) randomly determining the mode, quality level, and assignment order for each activity. (2) get a solution by improving the solution by changing the possible modes and quality levels; (3) to find a solution by improving the solution from the point where it is feasible to advance the start time. Here, Case[1] is a method to find the optimal solution value after repeating (1). Case [2] is a method for finding a solution including (1) and (2). Case [3] refers to a method for finding solutions including (1), (2), and (3). Results: It can be seen that the value of the objective function presented by the algorithm changes depending on how the model of the heuristic algorithm is designed and applied. In other words, it suggests the importance of algorithm design and proves the importance of the quality problem of activities in the project schedule. Conclusion: A study significance of the optimization algorithm and the heuristic algorithm was applied to the effect of the quality of the preceding activity on the duration and cost of itself and the succeeding activity, which was not addressed in the project schedule problem.

Adaptive Mean Value Cross Decomposition Algorithms for Capacitated Facility Location Problems (제한용량이 있는 설비입지결정 문제에 대한 적응형 평균치교차분할 알고리즘)

  • Kim, Chul-Yeon;Choi, Gyung-Hyun
    • Journal of Korean Institute of Industrial Engineers
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    • v.37 no.2
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    • pp.124-131
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    • 2011
  • In this research report, we propose a heuristic algorithm with some primal recovery strategies for capacitated facility location problems (CFLP), which is a well-known combinatorial optimization problem with applications in distribution, transportation and production planning. Many algorithms employ the branch-and-bound technique in order to solve the CFLP. There are also some different approaches which can recover primal solutions while exploiting the primal and dual structure simultaneously. One of them is a MVCD (Mean Value Cross Decomposition) ensuring convergence without solving a master problem. The MVCD was designed to handle LP-problems, but it was applied in mixed integer problems. However the MVCD has been applied to only uncapacitated facility location problems (UFLP), because it was very difficult to obtain "Integrality" property of Lagrangian dual subproblems sustaining the feasibility to primal problems. We present some heuristic strategies to recover primal feasible integer solutions, handling the accumulated primal solutions of the dual subproblem, which are used as input to the primal subproblem in the mean value cross decomposition technique, without requiring solutions to a master problem. Computational results for a set of various problem instances are reported.

Designing Cellular Mobile Network Using Lagrangian Based Heuristic (라그랑지안 기반의 휴리스틱 기법을 이용한 셀룰러 모바일 네트워크의 설계)

  • Hong, Jung-Man;Lee, Jong-Hyup
    • Journal of Korean Institute of Industrial Engineers
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    • v.37 no.1
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    • pp.19-29
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    • 2011
  • Cellular network is comprised of several base stations which serve cellular shaped service area and each base station (BS) is connected to the mobile switching center (MSC). In this paper, the configuration modeling and algorithm of a cellular mobile network with the aim of minimizing the overall cost of operation (handover) and network installation cost (cabling cost and installing cost of mobile switching center) are considered. Handover and cabling cost is one of the key considerations in designing cellular telecommunication networks. For real-world applications, this configuration study covers in an integrated framework for two major decisions: locating MSC and assigning BS to MSC. The problem is expressed in an integer programming model and a heuristic algorithm based on Lagrangian relaxation is proposed to resolve the problem. Searching for the optimum solution through exact algorithm to this problem appears to be unrealistic considering the large scale nature and NP-Completeness of the problem. The suggested algorithm computes both the bound for the objective value of the problem and the feasible solution for the problem. A Lagrangian heuristics is developed to find the feasible solution. Numerical tests are performed for the effectiveness and efficiency of the proposed heuristic algorithm. Computational experiments show that the performance of the proposed heuristics is satisfactory in the quality of the generated solution.

Development of forest carbon optimization program using simulated annealing heuristic algorithm (Simulated Annealing 휴리스틱 기법을 이용한 임분탄소 최적화 프로그램의 개발)

  • Jeon, Eo-Jin;Kim, Young-Hwan;Park, Ji-Hoon;Kim, Man-Pil
    • Journal of the Korea Society of Computer and Information
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    • v.18 no.12
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    • pp.197-205
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    • 2013
  • In this study, we developed a program of optimizing stand-level carbon stock using a stand-level yield model and the Simulated Annealing (SA) heuristic method to derive a optimized forest treatment solution. The SA is one of the heuristic algorithms that can provide a desirable management solution when dealing with various management purposes. The SA heuristic algorithm applied 'thermal equilibrium test', a thresholds approach to solve the phenomenon that does not find an optimum solution and stays at a local optimum value during the process. We conducted a sensitivity test for the temperature reduction rate, the major parameter of the thermal equilibrium test, to analyze its influence on the objective function value and the total iteration of the optimization process. Using the developed program, three scenarios were compared: a common treatment in forestry (baseline), the optimized solution of maximizing the amount of harvest(alternative 1), and the optimized solution of maximizing the amount of carbon stocks(alternative 2). As the results, we found that the alternative 1 showed provide acceptable solutions for the objectives. From the sensitivity test, we found that the objective function value and the total iteration of the process can be significantly influenced by the temperature reduction rate. The developed program will be practically used for optimizing stand-level carbon stock and developing optimized treatment solutions.

Applying Meta-Heuristic Algorithm based on Slicing Input Variables to Support Automated Test Data Generation (테스트 데이터 자동 생성을 위한 입력 변수 슬라이싱 기반 메타-휴리스틱 알고리즘 적용 방법)

  • Choi, Hyorin;Lee, Byungjeong
    • KIPS Transactions on Software and Data Engineering
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    • v.7 no.1
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    • pp.1-8
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    • 2018
  • Software testing is important to determine the reliability of the system, a task that requires a lot of effort and cost. Model-based testing has been proposed as a way to reduce these costs by automating test designs from models that regularly represent system requirements. For each path of model to generate an input value to perform a test, meta-heuristic technique is used to find the test data. In this paper, we propose an automatic test data generation method using a slicing method and a priority policy, and suppress unnecessary computation by excluding variables not related to target path. And then, experimental results show that the proposed method generates test data more effectively than conventional method.

An Experiment : Distribution of the Adversity Quotient as a Reduction of Bias in Estimating Earnings

  • Riza PRADITHA;Lasty AGUSTUTY;Robert JAO;Andi RUSLAN;Nur AISYAH;Diah Ayu GUSTININGSIH
    • Journal of Distribution Science
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    • v.21 no.6
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    • pp.99-106
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    • 2023
  • Purpose: This study aims to analyze the distribution of the role of adversity quotient in the estimation bias of future earnings. Adversity quotient is a cognitive ability that can be distributed as a reducer of bias effects that occur in profit forecasting or investment decision making. Research design, data and methodology: The study designs a full factorial within-subject 2×3 as a laboratory experiment. The study subjects are 30 accounting students who are proxied as investors. Results: The results show that the estimated earnings made by investors experience anchoring-adjustment heuristic bias which means the initial value becomes a basic belief that influences the decisions taken by investors. However, this study also provides evidence that heuristic bias can be reduced by the presence of adversity quotient. Investors who have high adversity ability are abler to reduce the estimation bias when compared to investors who have medium and low adversity ability so the higher the difficulty ability possessed by investors, the less likely the occurrence of bias in decision making. Conclusion: Thus, the adversity quotient is proven to be distributed as a reducing opportunity from the bias that will occur in estimating future earnings or making investment decisions.

Soccer league optimization-based championship algorithm (SLOCA): A fast novel meta-heuristic technique for optimization problems

  • Ghasemi, Mohammad R.;Ghasri, Mehdi;Salarnia, Abdolhamid
    • Advances in Computational Design
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    • v.7 no.4
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    • pp.297-319
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    • 2022
  • Due to their natural and social revelation, also their ease and flexibility, human collective behavior and teamwork sports are inspired to introduce optimization algorithms to solve various engineering and scientific problems. Nowadays, meta-heuristic algorithms are becoming some striking methods for solving complex real-world problems. In that respect in the present study, the authors propose a novel meta-innovative algorithm based on soccer teamwork sport, suitable for optimization problems. The method may be referred to as the Soccer League Optimization-based Championship Algorithm, inspired by the Soccer league. This method consists of two main steps, including: 1. Qualifying competitions and 2. Main competitions. To evaluate the robustness of the proposed method, six different benchmark mathematical functions, and two engineering design problem was performed for optimization to assess its efficiency in achieving optimal solutions to various problems. The results show that the proposed algorithm may well explore better performance than some well-known algorithms in various aspects such as consistency through runs and a fast and steep convergence in all problems towards the global optimal fitness value.

An Improved Particle Swarm Optimization Algorithm for Care Worker Scheduling

  • Akjiratikarl, Chananes;Yenradee, Pisal;Drake, Paul R.
    • Industrial Engineering and Management Systems
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    • v.7 no.2
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    • pp.171-181
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    • 2008
  • Home care, known also as domiciliary care, is part of the community care service that is a responsibility of the local government authorities in the UK as well as many other countries around the world. The aim is to provide the care and support needed to assist people, particularly older people, people with physical or learning disabilities and people who need assistance due to illness to live as independently as possible in their own homes. It is performed primarily by care workers visiting clients' homes where they provide help with daily activities. This paper is concerned with the dispatching of care workers to clients in an efficient manner. The optimized routine for each care worker determines a schedule to achieve the minimum total cost (in terms of distance traveled) without violating the capacity and time window constraints. A collaborative population-based meta-heuristic called Particle Swarm Optimization (PSO) is applied to solve the problem. A particle is defined as a multi-dimensional point in space which represents the corresponding schedule for care workers and their clients. Each dimension of a particle represents a care activity and the corresponding, allocated care worker. The continuous position value of each dimension determines the care worker to be assigned and also the assignment priority. A heuristic assignment scheme is specially designed to transform the continuous position value to the discrete job schedule. This job schedule represents the potential feasible solution to the problem. The Earliest Start Time Priority with Minimum Distance Assignment (ESTPMDA) technique is developed for generating an initial solution which guides the search direction of the particle. Local improvement procedures (LIP), insertion and swap, are embedded in the PSO algorithm in order to further improve the quality of the solution. The proposed methodology is implemented, tested, and compared with existing solutions for some 'real' problem instances.